Numerical Study on Spatio-Temporal Distribution of Cold Front-Induced Waves along the Southeastern Coast of China

Cold fronts, as one of the most frequent extreme weather events, can induce significant waves on the sea. This work analyzes the spatial and temporal variations in cold front events, especially the characteristics of wind directions during cold fronts in the East China Sea (ECS). The SWAN (Simulating Waves Nearshore) model is applied to simulating the waves induced by cold fronts. To calibrate the model, two typical cold front events were selected to simulate the corresponding waves in the ECS. The results indicate that the data misfit between the observed and modeled significant wave heights (SWH) is within a reasonable range. Idealized sensitivity experiments were then designed in order to analyze and discuss the responses of ocean waves to wind direction, swell distribution, maximum of significant wave heights (MSWH), and time lag during the cold fronts. The results show that the average MSWH in the ECS decreases monotonically with the deflection of wind direction from north-east to north-west, while specific nearshore sites do not conform to this pattern due to topography. The time series of SWH indicate that the action of the swells leads to a prolongation of the duration of catastrophic waves. This work investigates the temporal and spatial distribution characteristics of cold front-induced wind wave fields in offshore Zhejiang, which has important value for the study of the impact of cold fronts on the ocean as well as disaster prevention and mitigation efforts.

On Correlation between Wind and Wave Storms

The paper is focused on the formulation of an adequate criterion for associating wave storm events to the generating wind storm ones, and on the study of correlation between their characteristic parameters. In this context, the sea storm definition commonly used for storm identification from significant wave height data is adapted for wind storm, by processing wind speed data. A sensitivity analysis is proposed as function of the storm thresholds aiming at identifying optimal combination of wind speed and significant wave height thresholds allowing the association of relatively large number of events ensuring high correlation between wind and wave storm parameters. The analysis is carried out using as input data wind speeds and significant wave heights from four meteorological (buoys and anemometers) stations of the National Data Buoy Center moored off the East Coast of the United States. Results reveal that an optimal threshold combination is achieved assuming both wind speed and significant wave height threshold as 1.5 time their respective averages.

Modelling Short- and Long-Term Dependencies of Clustered High-Threshold Exceedances in Significant Wave Heights

The peaks-over-threshold (POT) method has a long tradition in modelling extremes in environmental variables. However, it has originally been introduced under the assumption of independently and identically distributed (iid) data. Since environmental data often exhibits a time series structure, this assumption is likely to be violated due to short- and long-term dependencies in practical settings, leading to clustering of high-threshold exceedances. In this paper, we first review popular approaches that either focus on modelling short- or long-range dynamics explicitly. In particular, we consider conditional POT variants and the Mittag–Leffler distribution modelling waiting times between exceedances. Further, we propose a new two-step approach capturing both short- and long-range correlations simultaneously. We suggest the autoregressive fractionally integrated moving average peaks-over-threshold (ARFIMA-POT) approach, which in a first step fits an ARFIMA model to the original series and then in a second step utilises a classical POT model for the residuals. Applying these models to an oceanographic time series of significant wave heights measured on the Sefton coast (UK), we find that neither solely modelling short- nor long-range dependencies satisfactorily explains the clustering of extremes. The ARFIMA-POT approach, however, provides a significant improvement in terms of model fit, underlining the need for models that jointly incorporate short- and long-range dependence to address extremal clustering, and their theoretical justification.

Numerical Analysis of the Effect of Binary Typhoons on Ocean Surface Waves in Waters Surrounding Taiwan

The ocean surface waves during Super Typhoons Maria (2018), Lekima (2019), and Meranti (2016) were reproduced using hybrid typhoon winds and a fully coupled wave-tide-circulation modeling system (SCHISM-WWM-III). The hindcasted significant wave heights are in good agreement with the along-track significant wave heights measured by the altimeters aboard the SARAL (Satellite with ARgos and ALtiKa) and Jason-2 satellites. Two numerical experiments pairing Super Typhoons Maria (2018) and Meranti (2016) and Super Typhoons Lekima (2019) and Meranti (2016) were conducted to analyze the storm wave characteristics of binary and individual typhoons. Four points located near the tracks of the three super typhoons were selected to elucidate the effects of binary typhoons on ocean surface waves. The comparisons indicate that binary typhoons not only cause an increase in the significant wave height simulations at four selected pints but also result in increases in the one-dimensional wave energy and two-dimensional directional wave spectra. Our results also reveal that the effects of binary typhoons on ocean surface waves are more significant at the periphery of the typhoon than near the center of the typhoon. The interactions between waves generated by Super Typhoons Maria (2018) and Meranti (2016) or Super Typhoons Lekima (2019) and Meranti (2016) might be diminished by Taiwan Island even if the separation distance between two typhoons is <700 km.

On the Occurrences of Critical Waves and Water Levels in the Venice Lagoon: A Statistical Analysis for the Management of the Operativity of the Mose System

The particular structure and configuration of the Venice lagoon represents a paramount case study concerning coastal flooding which affects natural, historical/cultural properties, together with industrial, commercial, economical and port activities. In order to defend Venice (and other sites) within the lagoon from severe floods, the Italian Government promoted the construction of a complex hydraulic/maritime system, including a movable storm surge barrier named Experimental Electromechanical Module (MoSE), to be activated when specific water levels occur. When the MoSE barriers are raised, the only access to the lagoon for commercial and cruise ships is represented by the Malamocco lock gate, provided that suitable safety conditions (involving the significant wave height) are satisfied. In addition, the Italian Government has recently established that, in the near future, large ships will always have to enter/exit the lagoon only through the Malamocco gate. In turn, the navigation within the Venice lagoon is (will be) controlled by the combined MoSE-Malamocco system, ruled by both univariate and bivariate paradigms/guidelines. As a novelty, in the present work, for the first time, the statistics of significant wave heights and water levels in the Venice lagoon (both univariate and bivariate ones) are investigated: in particular, these variables turn out to be dependent, and their joint occurrence (statistically modeled via Copulas) can determine the stop of ship navigation, yielding significant economic losses. Here, univariate and bivariate Return Periods and Failure Probabilities are used to thoroughly model the statistical behavior of significant wave heights and water levels, in order to provide useful quantitative indications for the management of the tricky hydraulic, maritime and economical system of the Venice lagoon.

Forecasting Hurricane-forced Significant Wave Heights using the Long Short-Term Memory Network in the Caribbean Sea

A Long Short-Term Memory (LSTM) neural network is proposed to predict hurricane-forced significant wave heights (SWH) in the Caribbean Sea (CS) based on a dataset of 20 CS, Gulf of Mexico, and Western Atlantic hurricane events collected from 10 buoys from 2010–2020. SWH nowcasting and forecasting are initiated using LSTM on 0-, 3-, 6-, 9-, and 12-hour horizons. Through examining study cases Hurricanes Dorian (2019), Sandy (2012), and Igor (2010), results illustrate that the model is well suited to forecast hurricane-forced wave heights. Forecasts are highly accurate with regard to observations. For example, Hurricane Dorian nowcasts had correlation (R), root mean square error (RMSE), and mean absolute percentage error (MAPE) values of 0.99, 0.16 m, and 2.6 %, respectively. Similarly, on the 3-, 6-, 9-, and 12-hour forecasts, results produced R (RMSE; MAPE) values of 0.95 (0.51 m; 7.99 %), 0.92 (0.74 m; 10.83 %), 0.85 (1 m; 13.13 %), and 0.84 (1.24 m; 14.82 %), respectively. However, the model also consistently over-predicted the maximum observed SWHs. To improve models results, additional research should be geared towards improving single-point LSTM neural network training datasets by considering hurricane track and identifying the hurricane quadrant in which buoy observations are made.

Round Robin Testing: Exploring Experimental Uncertainties through a Multifacility Comparison of a Hinged Raft Wave Energy Converter

The EU H2020 MaRINET2 project has a goal to improve the quality, robustness and accuracy of physical modelling and associated testing practices for the offshore renewable energy sector. To support this aim, a round robin scale physical modelling test programme was conducted to deploy a common wave energy converter at four wave basins operated by MaRINET2 partners. Test campaigns were conducted at each facility to a common specification and test matrix, providing the unique opportunity for intercomparison between facilities and working practices. A nonproprietary hinged raft, with a nominal scale of 1:25, was tested under a set of 12 irregular sea states. This allowed for an assessment of power output, hinge angles, mooring loads, and six-degree-of-freedom motions. The key outcome to be concluded from the results is that the facilities performed consistently, with the majority of variation linked to differences in sea state calibration. A variation of 5–10 % in mean power was typical and was consistent with the variability observed in the measured significant wave heights. The tank depth (which varied from 2–5 m) showed remarkably little influence on the results, although it is noted that these tests used an aerial mooring system with the geometry unaffected by the tank depth. Similar good agreement was seen in the heave, surge, pitch and hinge angle responses. In order to maintain and improve the consistency across laboratories, we make recommendations on characterising and calibrating the tank environment and stress the importance of the device–facility physical interface (the aerial mooring in this case).

HYDRODYNAMIC AND BOUSSINESQ WAVE MODELING FOR THE N219 AMPHIBIOUS AIRCRAFT SEAPLANE DOCK DEVELOPMENT PLAN IN PANJANG ISLAND

The flight test of N219 Amphibious aircraft will be targeted in 2003/2024. For flight tests, these aircraft need a seaplane dock. One of the potential locations for the seaplane dock is Panjang Island at Seribu Islands. This study aims to know the characteristic of hydrodynamic and wave conditions and to determine whether Panjang Island is suitable for the seaplane dock. This study uses a modeling method with MIKE 21 FM HD-SW module and MIKE 21 Boussinesq Wave (BW) module. The bathymetry data were obtained from the Indonesian Navy Hydrographic and Oceanographic Center (Pushidrosal), tide data is generated from Tide Model Driver (TMD), wave and wind data from ECMWF. The result of surface elevation validation between hydrodynamic modeling and TMD is 92%. During the west monsoon and spring conditions, the difference in the largest and lowest current velocity is quite large (0.018-0.199 m/s), on the other hand, when the tides are in neap conditions (0.008-0.144 m/s). Meanwhile, during the east monsoon and spring conditions, the difference in the largest and lowest current velocities is quite large (0.02-0.193 m/s), on the other hand, when the tides are in neap conditions (0.008-0.146 m/s). The maximum wave height resulting from the 50-year return period waveform modeling between 1.139 - 1.474 m. Meanwhile, the significant wave heights between 0.679 - 0.741 with a significant wave period of 13.45 seconds. In general, the current and wave conditions of the two locations are suitable for the construction of the seaplane dock, except that the dominant wave heights are still above the requirements.

Evaluation of hydromorphological conditions of Grand Popo Beach using two unique video cameras

Beaches are characterized by complex spatial and temporal patterns of erosion and accretion subjected to significant wave and tide influence. The objective of this study is to estimate the evolution of hydromorphodynamic conditions on the shoreline of Grand Popo Beach observed from two adjacent video camera setups. We have analyzed the impact of the variability of hydrodynamic parameters on the beach evolution and evaluated the variabilities of the hydrodynamic and morphologic parameters from the two cameras. Despite the nonhomogeneity within the cameras’ intrinsic properties, the various results obtained from the two systems indicate that wave conditions (peak period and significant height) from the cameras have the same variations, whereas the shoreline variations of camera A are not the same as those of camera B. It is generally during the summer that the Grand Popo Beach is exposed to an agitated environment with strong observed values of significant wave heights and wave energy flux, undoubtedly resulting in significant sediment transport along the beach leading a shoreline retreat. The results indicate that in 3.5 years the shoreline of Grand Popo Beach has retreated by 10 m.